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Machine Learning Tutorials
(w/ Python)

1- Linear Regression

Linear Regression Tutorials, Examples and Tips

2- Logistic Regression

Logistic Regression Tutorials and Examples

3- kNN

k Nearest Neighbor tutorial with explanation and examples

4- Naive Bayes

Naive Bayes Tutorials and Examples

5- Decision Trees

Decision Tree Tutorials & Examples

6- Random Forest

Random Forest tutorials, code example, explanation and tips and tricks

7- SVM

Support Vector Machines Tutorials, Tips, Examples

8- K-Means

K-Means clustering examples, history, advantages, disadvantages and optimization tips.

AI and Machine Learning is more popular than ever. Implementations of these technologies aren’t going anywhere, instead, they are being more and more utilized by companies and institutions. Depending on the perspective it can be an endless discussion of theory, mathematics, physics, sociology, philosophy, theology and even politics.

It can also be a practical technology that you can start using today.

I made these practical guides about different ML Algorithms in case there are people like me who like to mix top-down and bottom-up approaches when it comes to learning something new.

Each tutorial starts with a top-down approach and outright implementations, then some advanced knowledge…

The aim is to help as many people as possible to get familiar, use each algorithm for their own benefit or humanity in least possible time.

I hope you will take on Machine Learning challenges every day and discover amazing things.

Learn and explore as much as you’d like and create your own dreams and come up with your own style.

We hope you like the tutorials. Good luck and Enjoy!

HolyPython Team